Introductory MOOCs
- Machine Learning Foundations
- Carlos Guestrin and Emily Fox (University of Washington)
- Coursera
- My thoughts on the course and my exercises on Github
- Machine Learning
- Andrew Ng (Stanford)
- Coursera
- My exercises on Github
- Extended lectures on youtube
Neural Networks (and Deep Learning)
- Neural Networks and Deep Learning (ebook)
- A step by step propagation example (post)
- Getting started with Deep Learning and Python (post)
- Machine Learning Algorithms from Scratch with Python (book and links)
Links to check
http://www.datasciencecentral.com/profiles/blogs/deploying-predictive-models
http://www.datasciencecentral.com/profiles/blogs/why-so-many-machine-learning-implementations-fail
http://www.analyticbridge.com/profiles/blogs/regression-logistic-regression-and-maximum-entropy
http://www.analyticbridge.com/group/analyticaltechniques/forum/topics/logit-vs-probit-regression
http://www.analyticbridge.com/forum/topics/how-to-determine-if-a-sample-is-representative
http://www.datasciencecentral.com/profiles/blogs/naive-bayes-for-dummies-a-simple-explanation
http://www.datasciencecentral.com/profiles/blogs/correlation-does-not-imply-causation
http://www.datasciencecentral.com/profiles/blogs/simple-guide-for-selecting-statistical-tests-when-comparing
http://www.datasciencecentral.com/profiles/blogs/tutorial-how-to-detect-spurious-correlations-and-how-to-find-the-
http://www.datasciencecentral.com/profiles/blogs/12-algorithms-every-data-scientist-should-know
http://www.datasciencecentral.com/profiles/blogs/12-most-popular-data-science-blogs
http://www.datasciencecentral.com/profiles/blogs/40-techniques-used-by-data-scientists
https://www.quora.com/What-makes-a-model-interpretable/answer/Claudia-Perlich?srid=cgo
I feel as though I have wasted a lot of time forgetting the mathematics I was so good at once before, I love the article!!
I feel so very far behind i can’t wait to read more